Timely reaction to changing environments like markets and regulations is a severe challenge for globally acting enterprises. Therefore, fast informed decisions are essential for the success and the sustainability. Relevant data needs to be available in the right place at the right time. Exactly this is addressed by the FAIR Data principles by demanding data to be ndable, accessible, interoperable and reusable data. However, since its rst publication in 2016 [FOR18], it remains an open question, how FAIR Data can be realized. We are convinced that the set of Linked Data [Tim06] principles is the most promising solution to realize FAIR. Firstly, globally unique identi ers as described in the Findability aspect are realized in Linked Data by the consequent adoption of the Uniform Resource Identi er (URI) standard. Secondly, universal Accssibility through standard communication protocols is realized by making use of http. Thirdly, Interoperability is supported by focusing on leveraging RDF and SPARQL, which are developed for a distributed data space. And nally, as it is emphasized by its name, linking to existing datasets is the most crucial part of Linked Data, which addresses the Reusability aspect of FAIR Data.
Metadata Ontology: Metadata is core to FAIR data. To achieve this with the Linked Data principles, a metadata ontology is required. This must include properties like: Security classi cation, identi er of the resource, information about the creator and about the provenance.
Search Engine: To nally make the (meta)data ndable, a search engine is required. In case all of this services are provided, a FAIRness degree of 100% is achieved.
Internal Licensing and Certi cation Process: The certi cation should be issued by an recognized body and expresses whether a resource is compliant. A company would have to set up a process for the licences and certi cations. Evaluation and Conclusion In order to evaluate to what extend Linked Data and the additional services as described above are supporting the realization of the FAIR Data principles we utilized the FAIR Data metrics [Mar18]. The following table illustrates the comparisson of a dataset stored in a sheet, an RDF dataset and a dataset stored in a triplestore supported with the above mentioned services ful lls the FAIR Data metrics. This evaluation demonstrates clearly that every aspect of the FAIR Data metrics are ful lled. However, the metrics themselves are still work in progress. Therefore, this evaluation depends on the acceptance of these metrics. It might worth repeating the evaluation, as soon as the FAIR Data metrics are nalized.
Realizing FAIR Data in an Enterprise Environment